Millimeter waves are electromagnetic radiation characterized by wavelengths in the range of from 1 to 10 millimeters and having corresponding frequencies in the range of 300 GHz to 30 GHz. Millimeter waves have the capability of passing through some types of objects which would stop or significantly attenuate the transmission of electromagnetic radiation of other wavelengths and frequencies. For example, millimeter waves pass through clothing with only moderate attenuation, pass through doors and walls, are capable of penetrating slight depths of soil, and are not obscured or adversely influenced by fog, cloud cover and some other types of visually-obscuring meteorological conditions. Because of these properties, millimeter wave imaging has been employed to detect contraband and weapons concealed beneath clothing of an individual, to alert law enforcement authorities of the location of individuals and objects within the interior of a room or building prior to executing search warrant raids, to detect the presence and location of buried land mines, and for landing and takeoff guidance for aircraft when meteorological conditions obscure runways, among many other things.
According to known laws of physics, the amount or intensity of electromagnetic energy emitted by an object is proportional to its physical temperature measured in degrees Kelvin. The radiation originates from thermally-induced charged-particle accelerations, subatomic particle interactions and other quantum effects. These quantum effects account for a distribution of radiation throughout a broad spectrum of frequencies, as recognized by Planck's Law. Consequently, it is typical to characterize the amount of energy emanating from a point or object in a scene by its apparent brightness temperature.
The energy emanating from a point or object in the scene results from emission and reflection. Emission and reflection are related to one another such that highly emissive objects are only slightly reflective, and highly reflective objects are only slightly emissive. Passive millimeter wave imaging creates an image from both the emitted and the reflected electromagnetic energy. Active millimeter wave imaging also relies on energy emission and reflection, but enhances the energy content in a scene by illuminating the scene with added energy. The added energy increases the contrast or distinction in energy emanated from different points within the scene, primarily by increasing the reflected energy. Because passive millimeter wave imaging relies on the inherent natural energy emanating from the objects and the background in the scene, and such inherent natural energy is generally less than the amount of energy resulting from actively illuminating the scene with added energy, it is typically more difficult to create an image passively.
In some scenes, the distinction between the brightness temperature of an object and the brightness temperature of the background is relatively small. Slight differences in the brightness temperature of the objects and the background increase the difficulty of detecting those energy differences with enough distinction to create images with good contrast and resolution relative to the background. Inadequate contrast, resulting from an inability to detect relatively small differences in radiated energy from point to point within the scene, degrades the quality of the image. The ability to form good millimeter wave images is therefore directly related to the ability to recognize relatively small differences in the amount of millimeter wave energy emanated from different points within the scene, which is particularly important in passive millimeter wave imaging because of the relatively small differences in energy emanated from objects in the scene.
Millimeter wave imaging is further complicated by the fact that millimeter wave energy constitutes only a very small band or part of the spectrum of energy emitted by a body. The temperature-related quantum effects result in an energy distribution throughout a wide spectrum of frequencies. For millimeter wave imaging, only the frequency spectrum of radiation within the millimeter wavelength (30-300 GHz) is examined. Moreover, the typical millimeter wavelength frequency band used in millimeter wave imaging is even further restricted, for example, at 94±2 GHz. The amount of energy available is generally related to the bandwidth. Consequently, the limited bandwidth also reduces the amount of energy available to be detected for use in creating millimeter wavelength images.
Further complications arise from the noise-like origin of the millimeter wavelength energy which is detected to create the images. The thermally induced quantum effects result in a significant variations in frequency distribution and intensity of the emitted energy, thereby causing the radiated energy to have random characteristics similar, to noise. In the usual sense, noise is considered as a factor which contaminates or derogates an otherwise pure signal. The relatively pure nature of the underlying signal assists in distinguishing the corrupting noise and eliminating its effects, in typical signal processing. However, there is no underlying pure signal in passive millimeter wave imaging, due to the thermally induced and random quantum effects which create the emitted radiation. Consequently, it is necessary to rely on a primary noise-like signal for the information to create the image, and to attempt to eliminate or reduce the effects of other noise-like signals that have the potential to obscure the desired information from a primary signal. Thus, distinguishing the desired information carried by a noise-like signal from spurious and derogating noise-like signals of similar characteristics is a significant challenge in millimeter wave imaging.
The noise-like origin and characteristics of natural millimeter wave radiation, the limited bandwidth of energy within the millimeter wavelength spectrum from which to form the image, the relatively small differences in brightness temperature of the object in a scene compared to its background, and many other factors, have indicated a capability to enhance millimeter wave imaging by using multiple channels (radiometer channels are typically used for passive imaging and receiver channels are typically used for radar and most types of active imaging, although radiometer channels may be used in certain instances for non-radar active imaging), arranged in a focal plane array and scanning the energy emanating from the scene into the multiple channels. The channels convert the received or scanned-in radiant energy into electrical output value signals or samples. The multiple output values or samples from multiple different channels scanning each point are added together to create a pixel in the image which corresponds to that point in the scene. Each pixel has an intensity which is derived from adding the multiple samples.
One disadvantage of using multiple radiometer channels or receiver channels to obtain the multiple samples to be added together is that each channel has its own individual and particular response characteristics. In response to viewing exactly the same point having one brightness temperature, each channel creates a slightly different output value. When the slightly different samples from the multiple channels are combined to create each pixel, the intensity of the pixel does not faithfully represent the brightness temperature of the corresponding point in the scene. Adding signals which are slightly different, even when those signals originate from a single point in the scene with a uniform brightness temperature, results in slight derogation in contrast of the image. Such image derogation is not related to the energy content of the scene, but is related to the slightly different characteristics of the channels used to obtain the samples. Moreover because of the scanning effect, the anomalous effects introduced by the individual and different characteristics of each channel are distributed among various different pixels in the image, thereby decreasing the contrast and the quality of the image.
Despite careful efforts to make each radiometer and receiver channel exactly the same, each channel has its own unique gain, offset and noise temperature and response characteristics. Gain refers to the capability of the channel to amplify input signals it receives. Each channel characteristically amplifies a known constant input signal by a slightly different amount. Offset refers to a characteristic output signal level of the channel in response to a known input signal. The output signal level from each channel will be slightly different in magnitude in response to a known uniform input signal. The noise temperature characteristics of a channel relate primarily to electrical imperfections of components used in the channel, as opposed to the physical temperature of the channel itself. The noise temperature is extremely high relative to physical thermal temperature, and each channel has a significantly different noise temperature even when the physical temperature of the channels is maintained uniform.
To counteract the effects of the individual response characteristics of each channel, it is traditional to position a mechanical chopper in the optical path between the scene energy and the channels. The chopper periodically and rapidly introduces a known uniform brightness element, such as a black body, into the optical path, and each channel is quickly readjusted while the uniform brightness element is momentarily inserted in its optical path. The use of such choppers, and the necessity to quickly readjust each channel while still measuring radiation from the scene, greatly complicates the imaging process and the equipment necessary to perform the imaging.
To avoid the use of choppers, efforts have been made in the past to normalize the gain response characteristics of each channel. Normalization involves dividing the output response of each channel by the gain of the channel. In this manner, the response of each channel is gain normalized, so that when the samples from the channels are added, their contributions are of uniform relativity based on gain. While gain normalization has enhanced the quality of the image, gain normalization has not eliminated image anomalies arising because of the particular differences in offset and noise temperature characteristics of the channels. Moreover, the typical type of gain normalization employed in the prior art has been discovered not to account adequately for all variations in gain among the different channels.